The present disclosure relates to natural language processing systems, and more specifically to identifying one or more substitute ingredients for one or more particular recipes in a natural language processing (NLP) system.
Recent research has been directed to developing cognitive computing systems (e.g., concept expansion systems, question answering (QA) systems, etc.) that utilize NLP. Cognitive computing systems may build knowledge and learn (e.g., via training), understand natural language, reason, quickly identify new patterns, put content in context with confidence scores, analyze terms and interpret the terms' meanings, all of which may ultimately model intelligence. For example, QA systems may be designed to receive input questions, analyze them, and return applicable candidate answers. These systems may rely on NLP, automated reasoning, machine learning, and other advanced techniques. Using these techniques, QA systems may provide mechanisms for searching large sources of content and analyzing the content with regard to a given input question in order to determine an answer to the question. In some QA systems this may take the form of hypothesis generation, scoring, and ranking in order to determine a final set of one or more output answers.